Macro-Stress Testing NPLs in the Banking Sector in Namibia

Reinhold Kamati, A. William, G. Kadhikwa, Postrik Mushendami
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Abstract

This paper examined the impact of macroeconomic variables, namely real GDP growth, house price growth and changes in the repo rate on the non-performing loan (NPL) ratio in Namibia using data from 2004Q1 to 2020Q1. The study used a vector auto-regressive (VAR) model and impulse response analysis to estimate the impact of changes in macroeconomic conditions on NPLs, and further conducted stress testings on NPL ratio over 4 - 6 quarter horizons. Empirical evidence from this study shows that macroeconomic variables such as real GDP growth rate, the house price growth rate and the repo rate have a statistically significant impact, and material impact on the non-performing loans in the banking sector in Namibia. Largely, a positive growth rate shock in a quarter will reduce NPL ratio by more than half percentage point over two quarters. Similarly, a positive shock of about 4.0 percent in a quarter will reduce NPL ratio by more than 1.2 percentage points over four quarter horizons. Macro-stress-testing results revealed that a deterioration of the GDP growth rate by more than one standard deviation will increase the NPL ratio from 2.46 to 2.78 over four quarter horizons. Meanwhile, the combined effects of deteriorating the GDP growth rate and falling house prices further exacerbated the vulnerability of the banking sector. This study contributes to our understanding of the interplay between macroeconomic conditions and financial sector resilience in Namibia. In practical application, it shows that macro-stress testing techniques are useful to study the importance of macro-financial and feedback effects from the financial sector to the real economy. Technically, central banks must develop models that capture important macro-financial and feedback effects, and regulatory attention must be devoted to monitoring spillover effects from worsening financial conditions to the real economy.
纳米比亚银行业不良贷款的宏观压力测试
本文使用2004年第一季度至2020年第一季度的数据,研究了宏观经济变量(即实际GDP增长、房价增长和回购利率变化)对纳米比亚不良贷款率的影响。该研究使用向量自回归(VAR)模型和脉冲响应分析来估计宏观经济状况变化对不良贷款的影响,并进一步对4 - 6个季度的不良贷款率进行了压力测试。本研究的实证证据表明,实际GDP增长率、房价增长率和回购利率等宏观经济变量对纳米比亚银行业不良贷款的影响具有统计显著性,并具有实质性影响。在很大程度上,一个季度的正增长率冲击将使不良贷款率在两个季度内下降0.5个百分点以上。同样,季度内约4.0%的正面冲击将使不良贷款率在四个季度内减少逾1.2个百分点。宏观压力测试结果显示,GDP增长率恶化超过一个标准差,将使不良贷款率在四个季度内从2.46增加到2.78。与此同时,GDP增长率恶化和房价下跌的共同影响进一步加剧了银行业的脆弱性。这项研究有助于我们理解纳米比亚宏观经济条件与金融部门弹性之间的相互作用。实际应用表明,宏观压力测试技术有助于研究宏观金融的重要性以及金融部门对实体经济的反馈效应。从技术上讲,央行必须开发能够捕捉重要的宏观金融和反馈效应的模型,监管机构必须关注监测金融状况恶化对实体经济的溢出效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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